Browsing Faculty of Public Health, Nursing and Midwifery by Title
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- ItemPerformance of an open source facial recognition system for unique patient matching in a resource-limited setting(International Journal of Medical Informatics, 2020) Kitayimbwa, John M.; Were, Martin C.; Ampamyaa, SightBackground: The lack of unique patient identifiers is a challenge to patient care in developing countries. Probabilistic and deterministic matching approaches remain sub-optimal. However, affordable and scalable biometric solutions have not been rigorously evaluated in these settings. Methods: We implemented and evaluated performance of an open-source facial recognition system, OpenFace, integrated within a nationally-endorsed electronic health record system in Western Kenya. Patients were first enrolled via facial images, and later matched via the system. Accuracy of facial recognition was evaluated using Sensitivity; False Acceptance Rate (FAR); False Rejection Rate (FRR); Failure to Capture Rate (FTC) and Failure to Enroll Rate (FTE). 103 patients (mean age 37.8, 49.5% female) were enrolled. Results: The system had a sensitivity of 99.0%, FAR<1%, FRR 0.00, FTC 0.00 and FTE 0.00. Wearing spectacles did not affect performance. Conclusion: An open source facial recognition system correctly and accurately identified almost all patients during the first match.
- ItemPervasive and non-random recombination in near full-length HIV genomes from Uganda(Virus Evolution, 2020) Kitayimbwa, John M.; Grant, Heather E.; Hodcroft, Emma B.; Ssemwanga, Deogratius; Gonzalo, Yebra; Gomez, Luis Roger Esquivel; Frampton, Dan; Gall, Astrid; Kellam, Paul; Oliveira, Tulio de; Bbosa, Nicholas; Nsubuga, Rebecca N.; Kibengo, Freddie; Kwan, Tsz Ho; Lycett, Samantha; Kao, Rowland; Robertson, David L.; Ratmann, Oliver; Fraser, Christophe; Pillay, Deenan; Kaleebu, Pontiano; Brown, Andrew J. LeighRecombination is an important feature of HIV evolution, occurring both within and between the major branches of diversity (subtypes). The Ugandan epidemic is primarily composed of two subtypes, A1 and D that have been co-circulating for 50 years frequently recombining in dually infected patients. Here, we investigate the frequency of recombinants in this population and the location of breakpoints along the genome. As part of the PANGEA-HIV consortium, 1,472 consensus genome sequences over 5 kb have been obtained from 1,857 samples collected by the MRC/UVRI & LSHTM Research unit in Uganda, 465 (31.6 per cent) of which were near full-length sequences (>8 kb). Using the subtyping tool SCUEAL, we find that of the near full-length dataset, 233 (50.1 per cent) genomes contained only one subtype, 30.8 per cent A1 (n¼143), 17.6 percent D (n¼82), and 1.7 per cent C (n¼8), while 49.9 per cent (n¼232) contained more than one subtype (including A1/D (n¼164), A1/C (n¼13), C/D (n¼9); A1/C/D (n¼13), and 33 complex types). K-means clustering of the recombinant A1/D genomes revealed a section of envelope (C2gp120-TMgp41) is often inherited intact, whilst a generalized linear model was used to demonstrate significantly fewer breakpoints in the gag–pol and envelope C2-TM regions compared with accessory gene regions. Despite similar recombination patterns in many recombinants, no clearly supported circulating recombinant form (CRF) was found, there was limited evidence of the transmission of breakpoints, and the vast majority (153/164; 93 percent) of the A1/D recombinants appear to be unique recombinant forms. Thus, recombination is pervasive with clear biases in breakpoint location, but CRFs are not a significant feature, characteristic of a complex, and diverse epidemic.
- ItemPhylogenetic Networks and Parameters Inferred from HIV Nucleotide Sequences of High-Risk and General Population Groups in Uganda: Implications for Epidemic Control(Viruses, 2021) Kitayimbwa, John M.; Bbosa, Nicholas; Ssemwanga, Deogratius; Nsubuga, Rebecca N.; Kiwanuka, Noah; Bagaya, Bernard S.; Ssekagiri, Alfred; Gonzalo, Yebra; Kaleebu, Pontiano; Leigh-Brown, AndrewPhylogenetic inference is useful in characterising HIV transmission networks and assessing where prevention is likely to have the greatest impact. However, estimating parameters that influence the network structure is still scarce, but important in evaluating determinants of HIV spread. We analyzed 2017 HIV pol sequences (728 Lake Victoria fisherfolk communities (FFCs), 592 female sex workers (FSWs) and 697 general population (GP)) to identify transmission networks on Maximum Likelihood (ML) phylogenetic trees and refined them using time-resolved phylogenies. Network generative models were fitted to the observed degree distributions and network parameters, and corrected Akaike Information Criteria and Bayesian Information Criteria values were estimated. 347 (17.2%) HIV sequences were linked on ML trees (maximum genetic distance _4.5%, _95% bootstrap support) and, of these, 303 (86.7%) that consisted of pure A1 (n = 168) and D (n = 135) subtypes were analyzed in BEAST v1.8.4. The majority of networks (at least 40%) were found at a time depth of _5 years. The waring and yule models fitted best networks of FFCs and FSWs respectively while the negative binomial model fitted best networks in the GP. The network structure in the HIV-hyperendemic FFCs is likely to be scale-free and shaped by preferential attachment, in contrast to the GP. The findings support the targeting of interventions for FFCs in a timely manner for effective epidemic control. Interventions ought to be tailored according to the dynamics of the HIV epidemic in the target population and understanding the network structure is critical in ensuring the success of HIV prevention programs.